Search for a command to run...

Timestamps are as accurate as they can be but may be slightly off. We encourage you to listen to the full context.
This Odd Lots episode explores the intersection of AI technology and credit markets through a conversation with Dan Wertman, co-founder and CEO of Noetica AI. The discussion delves into how AI is being used to analyze complex deal documents and track evolving credit terms, while also examining concerning trends in private credit markets and AI financing structures. (07:00)
Dan Wertman is the co-founder and CEO of Noetica AI, a company that uses artificial intelligence to analyze deal documents and benchmark credit terms. He began his career at BlackRock developing financial products in fixed income markets, then earned his J.D. and worked as a corporate attorney at Wachtell Lipton from 2017-2022, where he handled major M&A transactions including T-Mobile's acquisition of Sprint and other multibillion-dollar deals.
Joe Wiesenthal is co-host of the Odd Lots podcast and a senior editor at Bloomberg. He focuses on markets, finance, and economic trends.
Tracy Alloway is co-host of the Odd Lots podcast and a senior editor at Bloomberg. She specializes in credit markets, structured finance, and alternative investments.
Both lenders and borrowers are increasingly seeking structural protections in deal terms, signaling growing market anxiety. (13:16) Wertman's data shows dramatic increases in protective terms: anti-PetSmart terms jumped from 4% in 2023 to 28% in Q3, while anti-Surda protections rose to 84% of deals - the highest ever recorded. This simultaneous fortification on both sides suggests market participants are preparing for potential distress scenarios, particularly given the looming maturity walls in 2027-2029 from debt issued during the 2020-2022 period.
The most telling trend is lenders' growing obsession with lien subordination terms, which govern payment priority during bankruptcy proceedings. (31:40) These recovery-focused protections reached 84% of deals in Q3, representing the biggest quarterly jump ever seen. This shift from preventing liability management exercises to controlling bankruptcy recovery suggests creditors may be anticipating actual distress events rather than just trying to prevent them.
Data center financing structures, exemplified by Meta's Hyperion deal with Blue Owl, involve 90% leverage on immature assets while keeping debt off corporate balance sheets. (40:23) These structures use special purpose vehicles where the operating company makes rent payments based on power costs, effectively creating circular financing arrangements. The combination of extremely high leverage, untested asset classes, and off-balance sheet treatment creates systemic risk that may not be fully understood by all market participants.
Large language models enable the first-time quantification of deal term prevalence by understanding semantic meaning rather than just exact text matches. (25:00) However, sophisticated parties continue to innovate with new terms in response to changing market conditions, as seen with the emergence of tariff-based default provisions and new outside date structures for regulatory uncertainty. This creates an ongoing arms race between AI detection capabilities and human legal creativity.
The expansion of private credit markets has made possible complex financing arrangements that would have been difficult to execute in traditional bank lending. (36:42) Companies like First Brands were able to access over $11 billion in total obligations through receivables financing facilities that weren't properly disclosed to other lenders. This opacity, combined with the market's depth, creates conditions where significant leverage can accumulate without full visibility to all stakeholders.